1. Field of the Invention
The present invention relates to a method for generating a high-quality multi-resolution three-dimensional model, and more particularly to a method for extracting feature lines based on texture images and geometric data from a three-dimensional model, which is generated using three-dimensional range scan data.
2. Description of the Related Art
As three-dimensional range scanning systems using complex three-dimensional models have been widely used. With a rapid development of the three-dimensional range scanning systems, even a complex shape of real objects can be measured quickly and accurately. The three-dimensional models measured are being used in a variety of applied fields, such as medical image processing, animation, games, and reverse engineering.
Feature lines are typically required to be extracted in a set of points in a diversity of fields, such as visualization of the three-dimensional models, geometric modeling, and computer graphics. This is why the feature lines play an important role in parts, such as mesh reconstruction, shape analysis, and model subdivision.
Meanwhile, features of a model shape are extracted for improvement in visualization of a set of points and converted into triangle meshes. Extracting the feature lines from the set of points is closely related to the reconstruction of a mesh surface. Extracting the feature lines from the set of points can be utilize as preprocessing for the mesh reconstruction. For example, a method of directly extracting the feature lines from three-dimensional mesh data must use different operators. These techniques require complex processes using mesh operators, etc., such as filtering, thinning, and smoothing. Implicit surface fitting technique shows a good result among those techniques, but there exists a drawback in that a process of computing feature extraction time is complex. This is why approximation and projection in all parts of implicit surface are used in order to measure the curvature tensor and a curvature differential value for each vertex of a mesh.
What is more, a method for extracting a feature in the form of a line from the set of points of the three-dimensional mesh data requires a complex process and technique related to a weight of a feature part, surface construction, a threshold value, and smoothing. It is problematic that a user who is unaccustomed to the method cannot obtain a good result because the user may achieve the desired result only after several attempts. For example, even though a multi-scale classification operator is applied to point-sampled data in order to search for features in the line-form, the operator cannot search for feature lines while precisely discriminating between a ridge and a valley line. For this, not only is it impossible that a multi-resolution three-dimensional model is generated, but also feature parts, which are important in the process of creating a three-dimensional model, are feasible all together.